Page 03/05/2020 09:26:53

James Audretch defendes his MSc Thesis

3/5/2020
‚ÄčAbstract

Earthquake detection is an important task, focusing on detecting seismic events in past data or in real time from seismic time series. In the past few decades, due to the increasing amount of available seismic data, research in seismic event detection shows remarkable success using neural networks and other machine learning techniques, which require strongly high quality labeled data sets. However, creating high quality labeled data sets is still a manual process that demands tremendous amounts of time and expert knowledge, and is stifling big data innovation. When compiling a data set, it is unclear how many earthquakes and noise are mislabeled. Another challenge is how to promote the general applicability of the machine learning based models to different geographical regions. In other words, the detection models trained by data sets from one location should be applicable to the detection at other locations.